The insurance industry is increasingly combining artificial intelligence, cloud communications and high-speed connectivity to modernize customer service, claims operations, workforce management and compliance. The shift is part of a broader insurtech transformation in which insurers are using software and data infrastructure across more stages of the insurance lifecycle.
Artificial intelligence is already being used in areas including underwriting, pricing, claims handling, customer service and fraud detection. The National Association of Insurance Commissioners (NAIC) says insurers remain responsible for complying with applicable insurance laws and consumer-protection requirements when AI supports business processes or decisions.
For insurers, the challenge is therefore not simply deploying new technology. Systems must also provide appropriate controls around data, cybersecurity, human oversight, documentation and accountability. Those requirements are becoming more significant as regulators develop frameworks for AI and third-party models.
What AI, Cloud Communications and 5G Mean for Insurtech
The technologies involved perform different functions but can operate as part of the same digital infrastructure.
AI can analyze conversations, summarize interactions, identify patterns and provide information to employees during customer engagements. Cloud communications connect voice, video, messaging and other customer channels through internet-based platforms. 5G connectivity can provide high-speed wireless connections for offices, remote employees and field operations.
Together, these technologies can create a more integrated operating environment.
The NAIC describes insurtech as technology that can simplify insurance processes, automate traditional practices and improve areas such as policy management and claims handling. It also identifies data privacy, cybersecurity, potential bias and transparency as important risks associated with greater technology adoption.
The distinction matters because AI does not replace the underlying responsibilities of an insurer. It becomes another component of an operating model that still requires governance and human accountability.
How Real-Time AI Is Being Used in Insurance
Customer interactions generate substantial amounts of information. Calls with policyholders, claims discussions, renewal conversations and service requests can contain details relevant to customer needs, operational performance and compliance.
AI-enabled communication platforms can process some of this information in real time.
Transcription and conversation analysis
Speech-to-text technology can convert customer calls into searchable records. AI systems can then analyze conversations for topics, sentiment, keywords or other predefined signals.
This can reduce the amount of manual work involved in reviewing interactions. It can also give supervisors a larger pool of information from which to assess service quality.
Agent assistance and coaching
AI systems can provide prompts or information while an employee is speaking with a customer. After an interaction, automated summaries and performance assessments can help managers identify areas for additional training.
The competitor material cites a potential reduction in coaching time of up to 75%. Such vendor-specific performance claims should be treated as dependent on the underlying implementation, workforce and measurement methodology rather than as a general industry result.
Claims and customer service
Claims operations are particularly information-intensive. AI-supported tools can help organize conversations, summarize case information and route customer requests.
However, automated outputs can contain errors. The NAIC notes that AI-generated information can sound accurate while being incorrect and emphasizes the continuing importance of human review, particularly for significant decisions.
Cloud Workspaces Are Connecting Distributed Insurance Teams
Insurance organizations increasingly operate through combinations of offices, contact centers, brokers, remote employees and field personnel.
A cloud communications platform can consolidate channels such as voice, video, messaging and SMS within a common environment. Integration with customer relationship management and productivity platforms can also connect communications with customer records and internal workflows.
This can reduce the need for employees to move between disconnected systems. More importantly, it can preserve context between different stages of a customer interaction.
Integrating communications with business systems
Connections with platforms such as Salesforce, HubSpot and Google Workspace can allow communication data to interact with customer and workflow information.
The resulting architecture can support:
- Customer-service records linked to communications
- Automated call summaries
- Internal collaboration between claims and service teams
- Workforce performance monitoring
- Centralized reporting
- Digital records for audit and compliance processes
The value depends on the quality of the underlying integrations and data controls. Connecting more systems also creates additional points that must be secured and governed.
5G Connectivity and Distributed Insurance Operations
5G is primarily a connectivity technology rather than an insurance-specific application. Its relevance to insurtech comes from the increasing number of employees, devices and applications that depend on reliable mobile networks.
For distributed insurance teams, high-speed connectivity can support cloud applications, video communication, mobile workstations and other data-intensive services.
Field-based employees may also depend on mobile connectivity when accessing customer information or submitting documentation outside traditional office environments.
The practical benefits will vary according to network availability, device capability, security architecture and the requirements of individual applications. A 5G connection by itself does not establish an organization’s cybersecurity or regulatory compliance.
AI Governance and Compliance Are Becoming Core Infrastructure Issues
Technology adoption in insurance is constrained by the industry’s regulatory responsibilities.
In the United States, the NAIC adopted its Model Bulletin on the Use of Artificial Intelligence by Insurance Companies in December 2023. The framework emphasizes that AI-supported decisions and activities must comply with applicable insurance laws and establishes expectations around governance and information that regulators may request during examinations or investigations.
The NAIC’s work has continued into 2026, including development of an AI Systems Evaluation Tool intended to help regulators assess insurers’ use of AI, governance arrangements, risk mitigation and data inputs. As of March 2026, the tool was being piloted by 12 participating states, according to the NAIC.
Europe has also developed a more detailed regulatory framework. EIOPA said in August 2025 that AI used for risk assessment and pricing in life and health insurance is classified as high-risk under the EU AI Act. EIOPA’s guidance also highlights data governance, record-keeping, fairness, cybersecurity, explainability and human oversight.
This means technology architecture increasingly has to accommodate governance requirements from the beginning rather than treating compliance as a separate administrative function.
Security, Data Privacy and Operational Risks
The expansion of AI-driven communications creates several risks that insurers need to manage.
Sensitive customer information
Insurance companies process personal and, in some circumstances, highly sensitive information. Moving communications and analytical workloads into cloud environments increases the importance of access controls, data retention policies and vendor oversight.
The NAIC continues to monitor how big data and AI affect privacy and the existing insurance regulatory framework.
AI errors and bias
AI systems can produce inaccurate outputs or reproduce problems contained in their training data or input datasets.
For insurance companies, this can have consequences beyond customer service if automated systems influence underwriting, pricing, claims or fraud-related decisions.
Regulators therefore increasingly focus on testing, documentation, fairness and human oversight. The NAIC’s current work specifically includes evaluation of AI systems and the data used as inputs.
Third-party technology dependence
Cloud communications, AI models and network services can involve multiple technology providers.
This creates additional questions around vendor risk, service availability, data handling, cybersecurity and responsibility when an automated system produces an incorrect result.
For insurers, a modern technology stack therefore requires governance across both internally developed systems and third-party services.
Costs and Operational Implications for Insurers
The financial impact of this technology extends beyond software subscription fees.
Insurers may need to allocate resources to:
- Cloud communications platforms
- AI software and computing capacity
- Network upgrades and connectivity
- Cybersecurity controls
- Data integration
- Employee training
- AI testing and monitoring
- Compliance documentation
- Vendor management
- System maintenance and integration
There can also be operational savings when repetitive administrative work is automated. But those savings depend on implementation quality, adoption by employees and the extent to which existing systems can be integrated.
The economic calculation is therefore broader than replacing one communications platform with another. It involves the cost of technology, governance and organizational change alongside potential improvements in productivity and service operations.
Future Outlook for Insurance Technology Infrastructure
The direction of the insurance technology market is toward greater integration between AI, cloud software, data systems and connectivity.
Regulatory developments suggest that governance will remain part of this transition. In the United States, regulators are developing tools to examine AI use by insurers. In Europe, sector-specific insurance rules operate alongside the EU AI Act, with particular attention to higher-risk applications.
This makes documentation, human oversight, cybersecurity and data governance increasingly important components of technology deployment.
The role of AI is also likely to extend beyond customer conversations. Current insurance applications already include underwriting, pricing, claims management and fraud detection, while communication platforms can provide another source of operational data.
The longer-term significance of AI, cloud communications and 5G will therefore depend not only on technical capabilities, but also on how insurers integrate those systems with existing processes and regulatory obligations.
Conclusion
AI, cloud communications and 5G are becoming interconnected components of the digital infrastructure used by insurance companies. AI can support conversation analysis, employee assistance and workflow automation, while cloud platforms can connect customer interactions across channels and 5G can support distributed operations.
The technology also introduces additional responsibilities. Data privacy, cybersecurity, AI accuracy, fairness, third-party risk and regulatory oversight remain significant considerations.
For insurers, the transition is consequently less about adopting individual technologies and more about building an operating environment in which digital tools can be used alongside appropriate governance, human oversight and regulatory controls.
